Processing methods for the detection of landmark acoustic cues

Abstract

Landmarks (Stevens, 2002) are acoustic cues that are correlated with certain changes in speech articulation, and can be used to infer some of the distinctive features useful for speech recognition, largely the manner features. This project identifies and organizes the processing steps involved in extracting eight types of Landmark acoustic cues for a feature-based hierarchical automatic speech recognition system, in which each module detects one landmark cue from samples of continuous speech, based on knowledge about human speech production and acoustic measurements such as formant frequency and energy. It maps out the processing steps necessary to accurately detect speech Landmarks, and describes a standardized system of modules implemented in Matlab that can accurately identify each of the Landmark cues in speech files quickly and efficiently. The processing methods laid out in this project provide a framework that can be later extended to find other acoustic cues related to place and voicing.